Yang Peng

Oct 26, 2024 | nature.com | Yang Peng

AbstractSR-like CTD-associated factor 8 (SCAF8) can regulate transcriptional termination, but the function of circSCAF8 remains unclear. In our study, we observed a significant increase in circSCAF8 expression in gastric cancer, particularly in tissues with lymph node metastasis. The Kaplan-Meier curve revealed that high circSCAF8 expression was associated with a low overall survival time in gastric cancer patients.

Sep 16, 2024 | ffnews.com | Lauren Towner |Yang Peng

Tottenham Hotspur has announced a new three-year strategic partnership with Ant International, a digital payment and financial technology leader. The partnership sees Ant International, together with its business brands Alipay+, Antom and WorldFirst, become the exclusive Official Global Payment Solutions and Digital Wallet Partner of Tottenham Hotspur, and Alipay+ the first Official Training Wear Sleeve Partner for both the men’s and women’s teams.

Mar 21, 2024 | biorxiv.org | Yang Peng |Yilin Li |Jia Shen |Jixing Ao

AbstractCervical adenocarcinoma (ADC) is more aggressive compared to other types of cervical cancer (CC), such as squamous cell carcinoma (SCC). The tumor immune microenvironment (TIME) and tumor heterogeneity are recognized as pivotal factors in cancer progression and therapy. However, the disparities in TIME and heterogeneity between ADC and SCC are poorly understood.

Jan 3, 2024 | dx.doi.org | li Liu |Yang Peng |Hua Zhu |Xuedan Jiang

We constructed a new ab initio potential energy surface (PES) for CO–N2O which includes the intramolecular Q3 normal coordinate for the N2O ν3 antisymmetric stretching vibration. The intermolecular potential was evaluated employing the supermolecular method at the [CCSD(T)]-F12a level, with the aug-cc-pVTZ basis set plus bond functions. By integral over the intramolecular Q3 coordinate, we obtained the vibrationally averaged PESs for the CO–N2O system in the ground and ν3 excited states of N2O.

Aug 17, 2023 | opg.optica.org | Wen Chen |Yang Peng

In this Letter, we propose a learning-based correction method to realize ghost imaging (GI) through dynamic scattering media using deep neural networks with Gaussian constraints. The proposed method learns the wave-scattering mechanism in dynamic scattering environments and rectifies physically existing dynamic scaling factors in the optical channel. The corrected realizations obey a Gaussian distribution and can be used to recover high-quality ghost images.